The use of wireless networks has become increasingly widespread. A wireless mobile station (e.g., a cellular telephone) that is used within a moving vehicle may be moving relatively fast with respect to a base transceiver station (BTS). It is common for a wireless mobile station within a moving vehicle to reach speeds of thirty miles per hour (30 mph) to fifty miles per hour (50 mph) or more. When a wireless mobile station is moving relatively fast, the signal level received at the base transceiver station (BTS) fluctuates rapidly due to the fast fading of the wireless propagation channel. The rapid fluctuations of the received signal level are created as the vehicle that is carrying the wireless mobile station rapidly passes by signal scattering structures such as buildings, large vehicles, or geological formations.
For example, a wireless mobile station in a vehicle transmits a signal that may proceed along a direct uplink path to the base station for a few seconds and then be largely blocked by a building for a few seconds as the vehicle passes the building. During blockage of the signal on such a direct path, a signal from the mobile station may travel along an indirect path by scattering off one of these scattering objects. The scattering by an object causes a reduction of the signal strength received at the base station due to greater propagation distance and due to absorption of power by the scattering surface.
In another scenario, a direct path signal and a scattered path signal arrive at the base station to combine out of phase to decrease the received signal strength. As the vehicle moves further, a direct path signal and a scattered path signal arrive at the base station to combine in phase to increase the received signal strength. Signal strengths of various multipaths of the signal on the uplink path rapidly increase and decrease in intensity as the vehicle continues to pass other buildings or structures.
In a similar manner, signal strengths of various multipaths of the signal from the base station to the mobile station (downlink path) rapidly increase and decrease in intensity as the vehicle continues to pass other buildings or structures. Those skilled in the art will recognize that fading of the signal in a vehicular environment can sometimes produce signal strength variations in excess of thirty decibels (30 dB) and significantly degrade system performance. Under such circumstances, many burst errors can occur within a relatively short time interval.
Several prior art techniques exist that are designed to alleviate this problem in existing traditional antenna systems (e.g., single antenna configuration, diversity antenna configuration). One such technique used in code division multiple access (CDMA) systems involves the use of convolutional coding and interleaving. Information bits at the mobile station are first encoded according to a coding scheme and then interleaved. The rate of the encoded bits is usually at least twice the rate of the information bits. The coded bits are then interleaved to spread the errors that are due to channel fading. At the receiver, the procedure is reversed. The coded bits are decoded and deinterleaved to obtain the information bits. However, this technique wastes available frequency bandwidth by introducing the extra redundant bits. Coding techniques are inefficient with respect to utilization of available bandwidth.
Space-time (ST) types of coding systems have been proposed for use with multiple antenna systems that are capable of achieving high bit rates within a bandwidth. These types of coding systems are well suited for low mobility environments such as indoor applications. However, they are not well suited for a mobile station within a vehicular environment where a mobile station moves rapidly with respect to a base transceiver station.
Another technique involves channel prediction and filtering. This technique predicts (i.e., estimates) the wireless channel using one of a variety of existing methods such as (1) blind estimation based on digital signal properties, (2) Kalman filtering based on signal correlation statistics, and (3) ray tracing based on electromagnetic wave propagation. This technique attempts to improve system performance by predicting the channel behavior and designing filters to eliminate the adverse effects of the channel. Channel prediction techniques require accurate modeling of the propagation environment and real time processing.
When an adaptive antenna array (AAA) is used at a base station transceiver, the spatial characteristics of the wireless channel are used to determine and evaluate the performance of the system. Similar to scalar propagation channels, the spatial channel characteristics of the wireless channel also fluctuate significantly due to fast fading when a mobile station is used within a vehicular environment. A spatial signature vector that includes spatial channel characteristics is used to describe the response of an antenna array to a mobile station. A spatial signature vector may also be referred to as a channel vector. For example, an “M by one” spatial signature vector for an antenna array with M antennas may take the form:
                              a          →                =                              ∑                          k              =              0                                      L              -              1                                ⁢                                          ⁢                                    α              k                        ·                                          v                →                            ⁡                              (                                  θ                  k                                )                                                                        (        1        )            where L is the number of multipath signals, αk is a complex path attenuation or fading coefficient of the kth multipath signal, {right arrow over (ν)} (θk) is a steering vector, and θk is a direction of arrival (DOA) of the kth multipath signal.
For fixed wireless applications, spatial signature vectors associated with each mobile station remain almost unchanged over time. An adaptive antenna array (AAA) system estimates the spatial signature of each mobile station from measurements made on the received uplink signal from the mobile station and then applies beamforming to each separate user signal, thereby increasing the capacity and improving the communication link quality and coverage.
As in the case previously described for non-adaptive antenna arrays, problems arise when a mobile station is moving relatively rapidly with respect to a base transceiver station. In such circumstances, the spatial signatures of the channel vary significantly within a short period of time for a mobile station. For example, the level-crossing rate of the amplitude vector for a mobile station traveling at twenty four kilometers per hour (24 kph) is greater than eighteen (18) per second. The amplitude change from the median power can approach negative thirty decibels (−30 dB).
There is, therefore, a need in the art for an improved system and method for improving uplink and downlink performance of an adaptive antenna array in a vehicular environment.